import pandas as pd
import matplotlib.pyplot as plt
from pandas import ExcelWriter
import os
import numpy as np
import random
plt.style.use("seaborn")

Healthy Samples

Parameters = pd.read_excel("D:/DATA SCIENCE/INTERNSHIP PROJECT/Modelling/HealthySamples.xlsx")

Parameters

	Unnamed: 0	Unnamed: 0.1	Patient	Sensor1_max	Sensor2_max	Sensor3_min	Latency	UES_start	UES_end	UES_Duration	Sample status
0	0	0	Control 1.txt	192.279698	113.474479	-20.601968	-0.028	1552.752	1553.392	0.640	Perfect
1	1	1	Control 1.txt	167.821012	98.336004	-11.776150	-0.028	1782.184	1782.896	0.712	Perfect
2	2	2	Control 1.txt	171.739528	249.844358	-24.181735	-0.036	611.556	612.284	0.728	Perfect
3	3	5	Control 1.txt	200.377661	107.578393	-16.358434	-0.092	2333.764	2334.412	0.648	Perfect
4	4	6	Control 1.txt	193.675898	105.770199	-25.335317	-0.172	1697.164	1697.784	0.620	Perfect
...	...	...	...	...	...	...	...	...	...	...	...
195	195	39	P24_F_27.txt	81.341268	161.707485	-13.554589	0.120	198.240	199.008	0.768	Perfect
196	196	49	P24_F_27.txt	82.632181	211.714351	-9.086748	0.276	192.688	193.624	0.936	Perfect
197	197	51	P24_F_27.txt	110.199130	167.292287	-21.098650	0.412	77.764	78.884	1.120	Perfect
198	198	56	P24_F_27.txt	83.648432	235.317006	-13.838407	0.120	195.080	195.940	0.860	Perfect
199	199	60	P24_F_27.txt	89.141680	184.495308	-14.048981	0.196	711.212	712.000	0.788	Perfect

200 rows × 11 columns

count = 1
for i in range(0, len(Parameters)):
    if Parameters.loc[i][10] == "Perfect":
        data = pd.read_excel("D:/DATA SCIENCE/INTERNSHIP PROJECT/Healthy/Samples/" + Parameters.loc[i][2][:-4] + "/" + Parameters.loc[i][2][:-4] + "_" + str(Parameters.loc[i][1]) + ".xlsx")
        data.Time = pd.to_numeric(data.Time, errors='coerce')
        data.Sensor1 = pd.to_numeric(data.Sensor1, errors='coerce')
        data.Sensor2 = pd.to_numeric(data.Sensor2, errors='coerce')
        data.Sensor3 = pd.to_numeric(data.Sensor3, errors='coerce')
        data.index = data.Time
        ax = data.plot.line(x='Time', y=["Sensor1", "Sensor2", "Sensor3"],figsize = (15, 8 ))
        b = data[data["Sensor1"] == Parameters.loc[i][3]]
        c = data[data["Sensor2"] == Parameters.loc[i][4]]
        d = data[data["Sensor3"] == Parameters.loc[i][5]]
        fro = data[data["Sensor3"] == data.loc[Parameters.loc[i][7]][4]]
        to = data[data["Sensor3"] == data.loc[Parameters.loc[i][8]][4]]
        b.plot.scatter(x="Time", y="Sensor1", ax=ax,color="r", marker="o",s=50)
        c.plot.scatter(x="Time", y="Sensor2", ax=ax,color="r", marker="o",s=50)
        d.plot.scatter(x="Time", y="Sensor3", ax=ax,color="r", marker="o",s=50)
        fro.plot.scatter(x="Time", y="Sensor3", ax=ax,color="b", marker="o",s=50)
        to.plot.scatter(x="Time", y="Sensor3", ax=ax,color="b", marker="o",s=50)
        print("Sample: ",count)
        plt.show()
        count = count + 1
    else:
        pass

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Unhealthy Samples

Parameters = pd.read_excel("D:/DATA SCIENCE/INTERNSHIP PROJECT/Modelling/UnHealthySamples.xlsx")

Parameters

	Unnamed: 0	Unnamed: 0.1	Patient	Sensor1_max	Sensor2_max	Sensor3_min	Latency	UES_start	UES_end	UES_Duration	Sample status
0	0	0	HD011C.txt	254.3694	113.88430	-9.446444	0.194	22.749	23.334	0.585	Perfect
1	1	1	HD011C.txt	183.8655	128.26630	-14.236160	0.216	6.871	7.552	0.681	Perfect
2	2	2	HD011C.txt	228.7961	141.95400	-8.533228	0.214	7.882	8.499	0.617	Perfect
3	3	3	HD011C.txt	240.5188	80.61724	-7.899569	0.188	13.298	13.891	0.593	Perfect
4	4	4	HD011C.txt	243.0201	122.63250	-18.783600	0.141	18.029	18.597	0.568	Perfect
...	...	...	...	...	...	...	...	...	...	...	...
197	197	477	HD11B.txt	209.1134	79.38563	-12.359970	0.192	61.255	61.856	0.601	Perfect
198	198	478	HD11B.txt	257.1539	64.76777	-12.154600	0.031	105.364	105.844	0.480	Correction
199	199	479	HD11B.txt	298.4223	28.70255	-16.952760	-0.132	37.756	38.331	0.575	Correction
200	200	480	HD11B.txt	306.7658	38.74133	-9.447460	0.140	74.398	74.974	0.576	Correction
201	201	481	HD11B.txt	309.8712	59.28852	-9.540810	0.110	10.308	10.866	0.558	Perfect

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count = 1
for i in range(0, len(Parameters)):
    if Parameters.loc[i][10] == "Perfect":
        data = pd.read_excel("D:/DATA SCIENCE/INTERNSHIP PROJECT/Unhealthy/Samples/" + Parameters.loc[i][2][:-4] + "/" + Parameters.loc[i][2][:-4] + "_" + str(Parameters.loc[i][1]) + ".xlsx")
        data.Time = pd.to_numeric(data.Time, errors='coerce')
        data.Sensor1 = pd.to_numeric(data.Sensor1, errors='coerce')
        data.Sensor2 = pd.to_numeric(data.Sensor2, errors='coerce')
        data.Sensor3 = pd.to_numeric(data.Sensor3, errors='coerce')
        data.index = data.Time
        ax = data.plot.line(x='Time', y=["Sensor1", "Sensor2", "Sensor3"],figsize = (15, 8 ))
        b = data[data["Sensor1"] == Parameters.loc[i][3]]
        c = data[data["Sensor2"] == Parameters.loc[i][4]]
        d = data[data["Sensor3"] == Parameters.loc[i][5]]
        fro = data[data["Sensor3"] == data.loc[Parameters.loc[i][7]][4]]
        to = data[data["Sensor3"] == data.loc[Parameters.loc[i][8]][4]]
        b.plot.scatter(x="Time", y="Sensor1", ax=ax,color="r", marker="o",s=50)
        c.plot.scatter(x="Time", y="Sensor2", ax=ax,color="r", marker="o",s=50)
        d.plot.scatter(x="Time", y="Sensor3", ax=ax,color="r", marker="o",s=50)
        fro.plot.scatter(x="Time", y="Sensor3", ax=ax,color="b", marker="o",s=50)
        to.plot.scatter(x="Time", y="Sensor3", ax=ax,color="b", marker="o",s=50)
        print("Sample: ", count)
        plt.show()
        count = count + 1
    else:
        pass

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